Data Manipulation (SQL/Python) Interview Questions
Practice 674 real Data Manipulation (SQL/Python) interview questions for 2026. Data Manipulation (SQL/Python) interview questions cover the core data work hiring teams use to judge day-one competence: translating product metrics into correct queries, handling edge cases (NULLs, late-arriving events, double-counting), writing efficient joins and window functions, and producing readable, reproducible Pandas code. Real interviews with detailed solutions in this category test both correctness and engineering judgment, not just syntax. Expect these questions across analytics and data-engineering loops at companies that weight practical querying heavily — especially Meta, Amazon, and TikTok. Interviewers evaluate problem scoping, test-case thinking, query performance, and clear communication of assumptions. For interview preparation, focus on hands-on practice: timed live SQL exercises, Pandas data-cleaning drills, and walking through tradeoffs when a naive query will be too slow. Practical habits that help in interviews include writing concise, well-commented queries, stating assumptions up front, and verifying results with small, explicit test cases.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Analyze Mission Outcomes and Allocate Response Units
Analyze Mission Outcomes and Allocate Response Units You receive historical mission-level data for a set of response units. Assume one row represents ...
Analyze Returning Borrowers Across Two Days of Logs
Analyze Returning Borrowers Across Two Days of Logs You receive two collections of loan-activity records, one for each of two consecutive days. Each r...
Calculate Daily Survey Response Rates by Country
The interview report preserved the survey tables and the request to calculate response rate, but not the exact grouping or output contract. The follow...
Describe How You Use SQL in Data Science Work
How do you use SQL in your day-to-day data-science work? Describe the kinds of problems you solve, the complexity of queries you can own, and the chec...
Describe Your Analysis and Visualization Toolkit
Give a recruiter-friendly overview of the data-analysis and visualization tools you use in your work. Explain what each tool helps you accomplish, how...
Implement and Evaluate Pin Similarity in Python
You are asked to compare Pin similarity in Python. Begin by clarifying how a Pin is represented and what “similar” should mean. Then assume the interv...
Query Top Played Tracks Globally And By Country
Given a play_events table with columns user_id, track_id, timestamp, and country, write SQL to return the top N most played tracks globally and the to...
Analyze User Ride Activity with SQL
Use the following tables to answer four SQL analysis tasks. `text rides(ride_id, ride_date, ride_rating, user_id) users(user_id, city) ` Constraints &...
Compare Survey Satisfaction for New and Established Users
The interview report preserved the survey tables and the request to compare response levels for new and old users, but it explicitly noted that the in...
Answer SQL And Data Warehouse Fundamentals For A Data Engineering Interview
Practice data engineering fundamentals across SQL set operations, anti-joins, top-N window queries, and warehouse modeling. The prompt covers UNION ve...
Measure Daily Late-Order Rates by Delivery Zone
The original interview report identified a late-order SQL exercise but did not preserve its exact schema. The following is a self-contained practice r...
Implement a Safe Average Function in Python
Write a Python function average(table) that returns the arithmetic mean of a list of numbers and returns 0 when the list is empty. Explain the functio...
Analyze Thirty-Day Ad Performance with SQL
Analyze Thirty-Day Ad Performance with SQL For this practice version, use the following neutral schema. clicked is a Boolean recorded on each impressi...
Compute a Rolling Seven-Day Revenue Sum with Missing Dates
Solve a PostgreSQL rolling-revenue problem that needs a complete daily series per seller, including no-order dates. It assesses UTC date handling, gap...
Find A Low-Quality Annotator From Label Data
Practice a pandas-style data analysis prompt for identifying a low-quality annotator from label data. The question emphasizes cleaning, agreement or g...
Compute Each Advertiser's Share of Shop Ad Spend
Compute Each Advertiser's Share of Shop Ad Spend You have the following daily advertising table: `text ads_detail( advertiser_id, ad_id, ad_type...
Debug ML pipeline and build text parser
You are in a hands-on, hour-long ML-engineering working session (Scale AI, Machine Learning Engineer loop). You are given a small ML project — data lo...
Analyze member video posting behavior by country
Question You are given two tables describing LinkedIn members and the videos they upload. Write SQL (and optionally Python where noted) to answer the ...
Debug and harden trial-assignment Python code
You are given the following simplified Python snippet used to assign users and trigger a 1‑month free trial: """ import random, datetime, requests def...
Calculate CTR and ad revenue
This question evaluates proficiency in data manipulation and analytics, specifically metric calculation (CTR) and multi-currency revenue aggregation, ...